Let us illustrate this.
In classical causal graphs, events are represented by random variables, in principle subject to intervention (Figure REF .a).
As we move from purely classical scenarios to more physical situations, like those involving quantum measurements, the formalism of causal structures is evolving
to focus on agents and on explicit physical transformations as carriers of causal influence, similarly to our approach.
For example, in the quantum causal structures of [1]}, events can correspond to quantum systems where agents can act locally (Figure REF .b).
Generally speaking, “events” embody a particular coarse-graining of a global picture into variables or subsystems of interest. As such, a single causal graph cannot reveal all the features of a complex theory — a different decomposition may explore new causal relations.Also, we can never know if we only have access to an effective state space, and there is a deeper theory that changes all the causal relations, e.g. by providing new common causes.
The choice of relevant nodes can be guided by operationalism: 1) we start by picking “variables” that we care about (like the outcomes of an experiment, or a subsystem corresponding to the perspective and range of intervention of an agent); 2) we then use Reichenbach's principle and independence conditions to complete the causal graph, by identifying further nodes and constraining the channels between them.E.g. in studying the process of coherent copy \(\alpha \vert 0 \rangle _A + \beta \vert 1 \rangle _A \rightarrow \alpha \vert 0 \rangle _B \vert 0 \rangle _C + \beta \vert 1 \rangle _B \vert 1 \rangle _C\)  in [1]}, we start with 3 nodes of interest \(A\) , \(B\)  and \(C\) , and are forced by Reichenbach's principle to complete the graph with a 4th node.
This procedure is similar in spirit to how in the present work we could start with the
description of a few agents and use secrecy and commutation constraints to identify other subspaces and transformations of interest, or build a notion of locality.
How successful we are in this endeavour depends largely on the (subjective) starting point — a poor initial choice of events or agents could make it impossible to find a meaningful causal graph or independent agents.
